A Prediction Technique For Agriculture With Hybrid Approach To Estimate Level Of Bioscience Using Machine Learning

Abstract

Developing countries like India mainly focused with agriculture which acts as back bone of Indian economy. Bioscience in the field of agriculture need to be improved in terms of Indian economy. Estimation of Bioscience leads to various research in the field of agriculture.  The main objectives of this research work is to predict the bioscience based on the food security, crop management, irrigation scheduling, harvesting and storage. This research work is mainly focused on the prediction model with two process. First one used to predict the yield based on the exiting data which includes temperature, rainfall, yield based ondecision tree. Second process used to estimate the irrigation schedule, soil water content and estimate the end session of the crop yield. This research work is enhanced with machine learning algorithm of optimized K-NN to estimate temperature, rainfall and yield. It’s also enhanced with machine learning algorithm Long Short Term memory which acts as a hybrid approach to provide an effective result.